US8244553B2 - Template development based on sensor originated reported aspects - Google Patents
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Definitions
- the present application is related to and claims the benefit of the earliest available effective filing date(s) from the following listed application(s) (the “Related Applications”) (e.g., claims earliest available priority dates for other than provisional patent applications or claims benefits under 35 USC ⁇ 119(e) for provisional patent applications, for any and all parent, grandparent, great-grandparent, etc. applications of the Related Application(s)). All subject matter of the Related Applications and of any and all parent, grandparent, great-grandparent, etc. applications of the Related Applications is incorporated herein by reference to the extent such subject matter is not inconsistent herewith.
- a computationally implemented method includes, but is not limited to providing one or more reported aspects associated with one or more source users that were originally reported by one or more sensors; and developing one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based at least on a portion of the one or more reported aspects.
- related systems include but are not limited to circuitry and/or programming for effecting the herein-referenced method aspects; the circuitry and/or programming can be virtually any combination of hardware, software, and/or firmware configured to effect the herein-referenced method aspects depending upon the design choices of the system designer.
- a computationally implemented system includes, but is not limited to: means for providing one or more reported aspects associated with one or more source users that were originally reported by one or more sensors; and means for developing one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based at least on a portion of the one or more reported aspects.
- a computationally implemented system includes, but is not limited to: circuitry for providing one or more reported aspects associated with one or more source users that were originally reported by one or more sensors; and circuitry for developing one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based at least on a portion of the one or more reported aspects.
- a computer program product including a signal-bearing medium bearing one or more instructions for providing one or more reported aspects associated with one or more source users that were originally reported by one or more sensors; and one or more instructions for developing one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based at least on a portion of the one or more reported aspects.
- a method for providing relevant reported aspects that are relevant to achieving one or more target outcomes includes providing, using a processor, one or more reported aspects associated with one or more source users that were originally reported by one or more sensors; and developing one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based at least on a portion of the one or more reported aspects.
- FIGS. 1 a and 1 b show a high-level block diagram of a Computing Device 10 operating in a network environment.
- FIG. 2 a shows another perspective of the Sensor Originated Reported Aspect Providing Module 102 of the Computing Device 10 of FIG. 1 b.
- FIG. 2 b shows another perspective of the Template Development Module 104 of the Computing Device 10 of FIG. 1 b.
- FIG. 2 c shows one perspective of one of the Sensor Integrated Devices 40 of the exemplary environment 100 of FIGS. 1 a and 1 b.
- FIG. 2 d shows one perspective of the one or more sensors 240 *(e.g., one or more sensors 240 a , one or more sensors 240 b , or one or more sensors 240 c ) of the exemplary environment 100 of FIGS. 1 a and 1 b.
- FIG. 3 is a high-level logic flowchart of a process.
- FIG. 4 a is a high-level logic flowchart of a process depicting alternate implementations of the sensor originated reported aspect providing operation 302 of FIG. 3 .
- FIG. 4 b is a high-level logic flowchart of a process depicting alternate implementations of the sensor originated reported aspect providing operation 302 of FIG. 3 .
- FIG. 4 c is a high-level logic flowchart of a process depicting alternate implementations of the sensor originated reported aspect providing operation 302 of FIG. 3 .
- FIG. 4 d is a high-level logic flowchart of a process depicting alternate implementations of the sensor originated reported aspect providing operation 302 of FIG. 3 .
- FIG. 4 e is a high-level logic flowchart of a process depicting alternate implementations of the sensor originated reported aspect providing operation 302 of FIG. 3 .
- FIG. 4 f is a high-level logic flowchart of a process depicting alternate implementations of the sensor originated reported aspect providing operation 302 of FIG. 3 .
- FIG. 5 a is a high-level logic flowchart of a process depicting alternate implementations of the template developing operation 304 of FIG. 3 .
- FIG. 5 b is a high-level logic flowchart of a process depicting alternate implementations of the template developing operation 304 of FIG. 3 .
- FIG. 5 c is a high-level logic flowchart of a process depicting alternate implementations of the template developing operation 304 of FIG. 3 .
- FIG. 5 d is a high-level logic flowchart of a process depicting alternate implementations of the template developing operation 304 of FIG. 3 .
- FIG. 6 is a high-level logic flowchart of another process.
- FIG. 7 is a high-level logic flowchart of a process depicting alternate implementations of the presentation operation 606 of FIG. 6 .
- FIG. 8 is another high-level block diagram showing one implementation of the computing device 10 of FIG. 1 b.
- a recent trend that has enjoyed explosive popularity in the computing/communication field is to electronically record one's everyday activities, behaviors, thoughts, beliefs, traits, physical or mental states, physical characteristics, and other aspects of the person's everyday life onto an open journal.
- One place where such open journals are maintained is at social networking sites commonly known as “blogs” where one or more users may report or post every aspect of their daily lives.
- an “aspect,” as will be referred to herein may be in reference to any act, behavior, characteristic, user state or status, belief, and so forth, that may be associated with a user (e.g., a person including, for example, a network user such as a blogger or a social networking user).
- microblogging The process of reporting or posting blog entries is commonly referred to as “blogging.”
- a newer type of blogging that has become very popular in recent times is microblogging, otherwise known as “twittering” or “tweeting.”
- switching or “tweeting.”
- each of the microblogs that are posted are typically relatively short posts or entries, usually not more than 140 characters long.
- social networking sites may also allow users to maintain open journals and to allow users to easily update their personal information in real time. Such updates are typically made via, for example, social networking status reports otherwise known simply as “status reports.” These social networking sites allow a user to report or post for others to view the latest status or other aspects related to the user.
- sensors to detect and report on a wide variety of user aspects (i.e., aspects of a user).
- sensors that may be used for such purposes vary widely, ranging from well-known devices that can detect and report on various physiological parameters such as heart rate or blood pressure, to sensors that can detect certain user behaviors or activities such as toilet usage.
- sensors that may be employed in order to monitor or detect user activities include, for example, accelerometers, pedometers, global positioning systems or GPSs, and so forth.
- Such devices are already, in fact, being integrated into mobile computing/communication devices such as cellular telephones and smart phones.
- sensors are also being integrated into mobile computing/communication devices such as those that monitor environmental conditions.
- sensors include, for example, those that can measure atmospheric conditions such as air quality levels.
- sensors that can monitor and detect various physiological characteristics of users including those that can, individually or in combination, collect physiological data that may be used in order to determine the inferred mental states (or simply “mental states”) of users.
- sensors include, for example, functional near-infrared (fNIR) devices, functional magnetic resonance imaging (fMRI) devices, electroencephalography (EEG) devices, magnetoencephalography (MEG) devices, galvanic skin sensor devices, and so forth.
- sensors may be integrated into user devices such as automobiles, exercise machines, household appliances, and so forth that may be employed in order to detect and monitor their usage. There are also sensors that are currently available that can even monitor bathroom or toilet usage. All the above described sensors may be configured to provide their collected data through log entries such as entries made through social networking channels (e.g., microblogs).
- log entries such as entries made through social networking channels (e.g., microblogs).
- log entries e.g., microblogs, status reports, and so forth
- log entries e.g., microblogs, status reports, and so forth
- blogs, microblogs, and various social networking sites become increasingly popular, personal data collected through such means may be spread across multiple network sites making it even more difficult to exploit such potentially useful data.
- methods, systems, circuitry, and computer program products are provided for developing one or more templates that may facilitate one or more end users in achieving one or target outcomes when one or more emulatable aspects included in the one or more templates are emulated. More particularly, the methods, systems, circuitry, and computer program products may be designed to develop the one or more templates based, at least in part, on one or more reported aspects of one or more “source users” that were at least originally reported by one or more sensors. In some embodiments, the one or more templates may be developed based on reported aspects that are reported by one or more sensors and one or more source users.
- one or more reported aspects that were at least originally reported by one or more sensors may at least initially be provided.
- the providing of the one or more reported aspects that were originally reported by one or more sensors may involve acquiring or retrieving of such reported aspects from, for example, a wireless network, a wired network, and/or a memory.
- the methods, systems, circuitry, and computer program products may be implemented by a variety of computing/communication devices including, for example, a network device such as a server (e.g., network servers) or a local client device (e.g., a source user device or an end user device).
- the one or more reported aspects that are provided by the methods, systems, circuitry, and computer program products may be used in order to develop one or more templates.
- a “template” is a plan or a schedule that is designed to facilitate the achievement of one or more target outcomes when one or more emulatable aspects included in the template are emulated.
- the one or more emulatable aspects that may be included in the template may correspond to the one or more reported aspects that were provided and that were originally reported by one or more sensors.
- a “personalized plan” is a particular type of template that has personalized for a particular end user.
- a personalized plan may be developed by taking a generic template and modifying the generic template (e.g., modifying or replacing the emulatable aspects that may be included in the generic template) such that the modified generic template (e.g., personalized plan) meets or satisfies logistical or physical limitations of the end user.
- An example of a personalized plan (or a template) is a personalized plan (or a template) that is developed based on reported aspects of a source user that facilitates an end user to achieve a desired outcome such as weight loss, achieving a high score on the scholastic aptitude test (SAT).
- SAT scholastic aptitude test
- a template may merely indicate a collection of activities (e.g., emulatable aspects) or may indicate a more precise schedule of activities (e.g., emulatable aspects) that an end user may emulate in order to achieve a target outcome or outcome.
- activities e.g., emulatable aspects
- schedule of activities e.g., go jogging for 30 minutes on day 1, go swimming for 40 minutes on day 2, and so forth
- the end user may need to execute in order to achieve the weight loss.
- the template may be a schedule of when and what activities (e.g., read a particular book on day 1, work on math problems from a particular math book on day 2, and so forth) the end user may need to execute in order to achieve the high test score for the SAT.
- a template may include one or more emulatable intermediate outcomes that are associated with the target outcome or outcomes associated with the template.
- the template may indicate the amount of weight loss an end user should have achieved (e.g., in order to achieve the target outcome) after emulating, for example, one week, two weeks, or a month of emulatable aspects indicated by the template.
- a template may merely be a collection of one or more emulatable aspects that does not define any relationships between the emulatable aspects.
- a template designed to facilitate an end user to achieve relaxed state of mind may indicate two unlinked emulatable aspects, “get 8 hours of sleep each night,” and “don't drink caffeine beverages.” Such a template would not necessarily have any indication of relationship between the two emulatable aspects indicated by the template.
- an “aspect” may be any occurrence of any behavior, act, belief, characteristic, state, or any other facet associated with a source user or a group of source users.
- a “source user” may be any person, such as a microblogger, who may be the basis for one or more reported aspects. Note that a source user may not necessarily have to be the source for the one or more reported aspects that are related to the source user since reported aspects that are associated with a particular source user may be provided by other source users or by sensors.
- a “reported aspect” may be any aspect associated with a source user that has been reported by, for example, one or more sensors or by one or more source users. In some instances, such a reported aspect may be reported in the form of a log entry such as a microblog entry or a status report.
- a “relevant reported aspect,” in contrast, may be a reported aspect that is at least associated with one or more source users who have achieved one or more target outcomes (e.g., sought-after goals or desired outcomes). Alternatively, a “relevant reported aspect” may be a reported aspect that is relevant to achieving the one or more target outcomes. The relevancy of a reported aspect with respect to achieving the one or more target outcomes in some instances may be based on one or more relevancy factors as will be further described herein. Note that references in the following to “reported aspects” and “relevant reported aspects” will actually be in reference to data that indicate such information (e.g., data that indicate reported aspects and data that indicate relevant reported aspects) unless indicated otherwise.
- target outcome may be any type of desirable goal or result that may be sought by, for example, an end user.
- target outcomes include, for example, health-related outcomes such as weight loss or improved cardiovascular conditioning, athletic outcomes such as developing a particular athletic skill including being able to pitch a curve ball or achieving a particular golf handicap, physiological outcomes such as reduced blood pressure or blood glucose levels, social outcomes such as obtaining membership into an elite social club or attaining a particular social status, mental state outcomes such as achieving certain level of calmness or happiness, interpersonal or relational outcomes such as having lots of friends or developing skill to make friends, employment outcomes such as being promoted or developing certain work skills, academic or intellectual outcomes, and so forth.
- health-related outcomes such as weight loss or improved cardiovascular conditioning
- athletic outcomes such as developing a particular athletic skill including being able to pitch a curve ball or achieving a particular golf handicap
- physiological outcomes such as reduced blood pressure or blood glucose levels
- social outcomes such as obtaining membership into an elite social club or attaining a particular social status
- mental state outcomes such as achieving certain level of calm
- An “end user” may be any person who is a direct or indirect beneficiary of one or more templates that may be developed based at least in part on one or more reported aspects that may be provided by, for example, one or more sensors.
- a “source user” may be any person who may be the basis for one or more reported aspects. Note that although in most cases, a source user will be an actual (real) person who may be the basis for one or more reported aspects, in other cases, however, a source user may be a fictional person such as a composite of multiple “actual” source users. For example, reported aspects indicating actual aspects of a plurality of actual source users may be compiled and processed (e.g., normalized or averaged out) in order to create a fictional source user.
- FIGS. 1 a , and 1 b illustrating an example environment in which the methods, systems, circuitry, and computer program products in accordance with various embodiments may be implemented by a computing device 10 .
- the methods, systems, circuitry, and computer program products may be implemented at any network device including at a peer-to-peer network component device.
- the computing device 10 may be a server such as one of the one or more network servers 60 illustrated in FIG. 1 a .
- the computing device 10 may be a source user device such as one of the local source user devices 20 * illustrated in FIG. 1 a .
- the computing device 10 may be an end user device such as one of the local end user device 30 * illustrated in FIG.
- references in the following description to, for example, “a source user 2 *” may be in reference to a source user 2 a , a source user 2 b , and so forth.
- computing device 10 of the exemplary environment 100 of FIGS. 1 a and 1 b will be generally described in the following discussion operating as a server (e.g., server embodiment) rather than as an end user device or as a source user device. Further, although the following discussion related to the exemplary environment 100 of FIG.
- the computing device 10 may operate via a web 1.0 or web 2.0 construct.
- the computing device 10 may be a network device such as a server (e.g., a network server 60 ) that is designed to communicate with other network devices.
- the computing device 10 may communicate with one or more source users 2 *(e.g., source user 2 a , source user 2 b , and so forth) through one or more local source user devices 20 *(e.g., local source user device 20 a , local source user device 20 b , and so forth), with one or more end users 4 *(e.g., end user 4 a , end user 4 b , and so forth) through one or more local end user devices 30 *(e.g., local end user device 30 a , local end user device 30 b , and so forth), with one or more sensor integrated devices 40 (e.g., a transportation vehicle such as a car, an exercise machine, or any other type of device that may have an integrated sensor designed to sense, for example,
- sensor integrated devices 40 e.g., a transportation vehicle such as a car
- the wireless and/or wired network 50 may include at least one of a local area network (LAN), a wireless local area network (WLAN), personal area network (PAN), Worldwide Interoperability for Microwave Access (WiMAX), public switched telephone network (PTSN), general packet radio service (GPRS), cellular networks, and/or other types of wireless and/or wired networks 50 .
- LAN local area network
- WLAN wireless local area network
- PAN personal area network
- WiMAX Worldwide Interoperability for Microwave Access
- PTSN public switched telephone network
- GPRS general packet radio service
- cellular networks and/or other types of wireless and/or wired networks 50 .
- the computing device 10 may be designed to, among other things, provide (e.g., obtain, retrieve, receive, solicit, and so forth) one or more reported aspects 15 associated with one or more source users 2 * that were originally reported by one or more sensors 240 *. Based at least on a portion of the one or more reported aspects 15 that are provided, the computing device 10 may develop one or more templates 18 , the one or more templates 18 to be developed being designed to facilitate one or more end users 4 * to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates 18 are emulated.
- provide e.g., obtain, retrieve, receive, solicit, and so forth
- the computing device 10 may develop one or more templates 18 , the one or more templates 18 to be developed being designed to facilitate one or more end users 4 * to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates 18 are emulated.
- the computing device 10 may randomly, semi-continuously, or continuously acquire (e.g., receive, retrieve, or solicit) reported aspects 15 associated one or more source user 2 * that were at least originally reported by one or more sensors 240 *.
- Such reported aspects 15 may indicate a variety of aspects (e.g., behavior aspects such as user activities, user states, environmental conditions, and so forth) associated with the one or more source users 2 *.
- the reported aspects 15 to be acquired may, in some cases, include both reported aspects 15 that are relevant to achieving one or more target outcomes and reported aspects 15 that may not be relevant for achieving the one or more target outcomes.
- the reported aspects 15 may be acquired from a variety of sources.
- the reported aspects 15 that may be acquired by the computing device 10 may be acquired from one or more network servers 60 , from one or more local source user devices 20 *, from one or more sensor integrated devices 40 (e.g., exercise machine or an automobile with integrated sensors), from one or more third parties 6 (e.g., content providers, network service providers, and so forth), and/or from a memory 116 .
- the reported aspects 15 are acquired through a wireless network and/or a wired network 50
- the acquisition of the reported aspects 15 may be as a result of transmitting one or more solicitations for such data.
- the computing device 10 may develop one or more templates 18 that are designed to facilitate one or more end users 4 * to achieve one or more target outcomes, the development of one or more templates 18 based on at least a portion of the one or more reported aspects that are provided.
- the computer device 10 may be designed to identify from the one or more reported aspects 15 that have been provided, one or more relevant reported aspects 16 that are determined to be relevant for achieving the one or more target outcomes.
- this may mean at least identifying those reported aspects 15 that are associated with source users 2 * who have been identified as achieving the one or more target outcomes.
- a reported aspect 15 may be deemed relevant for achieving the one or more target outcomes when the reported aspect 15 is determined to be relevant with respect to certain relevancy factors as will be further described herein.
- one or more templates 18 may be developed by including into each of the one or more templates 18 , one or more emulatable aspects that corresponds to the one or more relevant reported aspects 16 .
- one or more relationships e.g., temporal, specific time, or spatial relationship between the multiple emulatable aspects may be defined in the template 18 .
- the computing device 10 may be configured to selectively provide (e.g., acquire) reported aspects 15 that are relevant for achieving one or more target outcomes.
- selectively acquiring relevant reported aspects 16 rather than acquiring reported aspects 15 that are associated with the one or more source users 2 * and that were originally reported by one or more sensors 240 * and that include both relevant reported aspects 16 and non-relevant reported aspects 17 .
- one or more templates 18 may be developed by the computing device 10 based directly on the provided reported aspects 15 (e.g., developing the one or more templates 18 by including into each of the one or more templates 18 one or more emulatable aspects that corresponds to one or more provided reported aspects 15 ) rather than having to filter through the reported aspects 15 in order to identify the relevant reported aspects 16 .
- the computing device 10 may be designed to present the one or more templates 18 .
- the one or more templates 18 may be presented by transmitting via the wireless network and/or wired network 50 the one or more templates 18 to one or more network servers 60 , to one or more source users 2 * (e.g., one or more local source user devices 20 *), to one or more end users 4 *(e.g., one or more local end user devices 30 *), and/or to one or more third parties 6 .
- the computing device 10 may indicate (e.g., visually display or audioally indicate) the one or more templates 18 via a user interface 120 .
- the development of the one or more templates 18 may include developing the one or more templates 18 based on one or more reported aspects 15 that are associated with one or more source users 2 * and that were originally reported by the one or more sensors 240 * and one or more reported aspects 15 that are associated with the one or more source users 2 * and that were originally reported by the source users 2 *.
- the one or more templates 18 may be developed based on data reported by one or more sensors 240 * and by one or more source users 2 *.
- the one or more reported aspects 15 that are provided by the one or more source users 2 * may have been provided through social networking entries such as blog or microblog entries, status reports, and so forth.
- the one or more sensors 240 * may include almost any type of sensors 240 * including, for example, sensors 240 * that can sense various physical characteristics of a source user 2 *(e.g., heart rate sensor or blood pressure sensor), sensors 240 * that can sense activities of a source user 2 *(e.g., a pedometer), sensors 240 * that can sense environment conditions (e.g., air quality sensors), sensors 240 * that can sense the location of a source user 2 *(e.g., global positioning system or GPS), sensors 240 * that can provide physiological data that may be processed in order to determine inferred mental states of users, and so forth.
- sensors 240 * that can sense various physical characteristics of a source user 2 *(e.g., heart rate sensor or blood pressure sensor), sensors 240 * that can sense activities of a source user 2 *(e.g., a pedometer), sensors 240 * that can sense environment conditions (e.g., air quality sensors), sensors 240 * that can sense the location of a source user 2 *(e
- the computing device 10 may be a server (e.g., one of the one or more network servers 60 ) that may be located at a single network site, located across multiple network sites, or may be a conglomeration of servers located at multiple network sites.
- a server e.g., one of the one or more network servers 60
- the computing device 10 may be any one of a wide range of mobile or stationary computing/communication devices including, for example, a laptop, a desktop, a workstation, a cellular telephone, a personal digital assistant (PDA), a Smartphone, a web tablet such as a Netbook, and so forth.
- a laptop e.g., local source user device 20 *
- an end user device e.g., local end user device 30 *
- the computing device 10 may be any one of a wide range of mobile or stationary computing/communication devices including, for example, a laptop, a desktop, a workstation, a cellular telephone, a personal digital assistant (PDA), a Smartphone, a web tablet such as a Netbook, and so forth.
- PDA personal digital assistant
- the one or more sensor integrated devices 40 may directly communicate with the wireless network and/or the wired network 50 in some embodiments.
- the one or more sensor integrated devices 40 may indirectly communicate with the wireless network and/or the wired network 50 via the one or more local source user devices 20 *(e.g., via, for example, personal area network or PAN).
- a sensor integrated device 40 may be a variety of devices that may comprise of one or more sensors 240 c and that may be operated or used by a source user 2 *.
- Examples of such devices include, for example, a transportation vehicle (e.g., automobile, a motorcycle, a boat, a plane, and so forth), an exercise machine (e.g., a treadmill), a household appliance (e.g., television set), and so forth.
- a transportation vehicle e.g., automobile, a motorcycle, a boat, a plane, and so forth
- an exercise machine e.g., a treadmill
- a household appliance e.g., television set
- each of the one or more sensor integrated devices 40 may include one or more sensors 240 c , a network interface 242 , a memory 243 , and/or one or more functional components 244 .
- the one or more sensors 240 c may be designed to detect or sense one or more aspects associated with one or more source users 2 * such as usage of the sensor integrated device 40 by, for example a source user 2 *.
- the one or more sensors 240 c may be designed to sense or monitor certain physical characteristics of a source user 2 * when the sensor integrated device 40 is being used for its functional purpose. For example, some exercise machines such as treadmills have sensors 240 * that can monitor the heart rate of, for example, a source user 2 * when the source user 2 * is using the treadmill.
- the computing device 10 , the one or more local source user devices 20 *, and the one or more sensor integrated devices 40 may include one or more sensors 240 *(e.g., one or more sensors 240 a for the computing device 10 , one or more sensors 240 b for the one or more local source user devices 20 *, and one or more sensors 240 c for the one or more sensor integrated devices 40 ) that are designed to detect or monitor various aspects of one or more source users 2 *.
- FIG. 2 d illustrates the types of devices that may be included in the one or more sensors 240 * of the computing device 10 , the one or more local source user devices 20 *, and the one or more sensor integrated devices 40 .
- the one or more sensors 240 * that may be included with the computing device 10 , the one or more local source user devices 20 *, and/or the one or more sensor integrated devices 40 may include one or more behavior aspect sensors 246 that are designed to sense one or more behavior aspects of one or more source users 2 *.
- Examples of sensing devices that may be considered behavior aspect sensors 246 include, for example, pedometers 247 , accelerometers 248 , exercise equipment sensors 249 , transport vehicle sensors 250 , household appliance sensors 251 , and toilet usage sensors 252 .
- sensing devices e.g., pedometers 247 and accelerometers 248 may directly detect activities of users (e.g., source users 2 *)
- other sensing devices such as exercise equipment sensors 249 and transport vehicle sensors 250 may only sense usage of the underlying devices (e.g., exercise equipment and transport vehicle).
- some sensors 240 * such as exercise equipment sensors 249 may include sensing devices for detecting physiological characteristics (e.g., heart rate) of users.
- the one or more sensors 240 * that may be included with the computing device 10 , the one or more local source user devices 20 *, and/or the one or more sensor integrated devices 40 may include one or more user physical characteristic sensors 253 that are designed to sense one or more physical characteristics of one or more source users 2 *.
- Examples of sensing devices that may be considered physical characteristic sensors 253 include, for example, image capturing devices 261 such as digital cameras or portable ultrasound devices (e.g., to capture internal or external images of source users 2 *), audio capturing devices (e.g., to capture voice or internal sound such as heart rate), and/or user physiological sensors 254 .
- physiological sensors 254 include, for example, fNIR devices, fMRI devices, heart rate monitors, blood pressure devices, blood glucose meters, and so forth. Note that some physiological sensors 254 may be used in order to obtain physiological data that may be processed using appropriate software in order to determine at last inferred mental states of users.
- the one or more sensors 240 * that may be included with the computing device 10 , the one or more local source user devices 20 *, and/or the one or more sensor integrated devices 40 may include one or more global position system (GPS) devices 255 that are designed to find the geographical locations of one or more source users 2 *.
- GPS devices 255 are now commonly integrated into many mobile communication devices such as cellular telephones and Smartphones.
- the one or more sensors 240 * that may be included with the computing device 10 , the one or more local source user devices 20 *, and/or the one or more sensor integrated devices 40 may include one or more user environmental condition sensors 256 that are designed to sense one or more environmental conditions associated with one or more source users 2 *.
- sensing devices that may be considered environmental condition sensors 256 include, for example, air quality sensors 257 designed to sense quality of air (e.g., pollutant amount, pollen count, gas level, and so forth) that one or more source users 2 * breathes, water quality sensors 259 designed to sense quality of water being drunk by one or more source users 2 *, and/or atmospheric condition sensors 258 that are designed to measure certain atmospheric conditions such as temperature, humidity, pressure, wind speed, and so forth.
- air quality sensors 257 designed to sense quality of air (e.g., pollutant amount, pollen count, gas level, and so forth) that one or more source users 2 * breathes
- water quality sensors 259 designed to sense quality of water being drunk by one or more source users 2 *
- atmospheric condition sensors 258 that are designed to measure certain atmospheric conditions such as temperature, humidity, pressure, wind speed, and so forth.
- the one or more sensors 240 * that may be included with the computing device 10 , the one or more local source user devices 20 *, and/or the one or more sensor integrated devices 40 may include one or more mental state sensors 260 that are designed to sense one or more physical or physiological characteristics of one or more source users 2 * that may be processed, using the appropriate software, in order to determine mental states of the one or more source users 2 *.
- mental state sensors 260 include, for example, fNIR devices, fMRI devices, EEG devices, MEG devices, galvanic skin sensor devices, and so forth.
- the one or more sensors 240 * that may be included with the computing device 10 , the one or more local source user devices 20 *, and/or the one or more sensor integrated devices 40 may include one or more image capturing devices 261 (e.g., digital camera, camcorder, ultrasound devices, and so forth) that may be employed in order to capture, for example, physical characteristics of one or more source users 2 *. Such devices may also be used in order to sense other types of aspects associated with one or more source users 2 *. For example, in some cases, image capturing devices 261 may be employed in order to detect or capture activities being executed by one or more source users 2 *. By using the appropriate software, images captured through such devices may be properly interpreted.
- image capturing devices 261 e.g., digital camera, camcorder, ultrasound devices, and so forth
- image capturing devices 261 may be employed in order to detect or capture activities being executed by one or more source users 2 *.
- each of the one or more local source user devices 20 * and each of the one or more local end user devices 30 *(as well as the computing device 10 in embodiments in which the computing device 10 is an end user device or a source user device) may be any one of a variety of computing/communication devices including, for example, a cellular phone, a personal digital assistant (PDA), a laptop, a desktop, or other types of computing/communication devices.
- PDA personal digital assistant
- the one or more local source user devices 20 * and/or the one or more local end user devices 30 *(as well as the computing device 10 in some embodiments) may be a handheld device such as a cellular telephone, a Smartphone, a Mobile Internet Device (MID), an Ultra Mobile Personal Computer (UMPC), a convergent device such as a personal digital assistant (PDA), and so forth.
- a handheld device such as a cellular telephone, a Smartphone, a Mobile Internet Device (MID), an Ultra Mobile Personal Computer (UMPC), a convergent device such as a personal digital assistant (PDA), and so forth.
- MID Mobile Internet Device
- UMPC Ultra Mobile Personal Computer
- PDA personal digital assistant
- such local client devices e.g., local source user device 20 * and/or local end user device 30 *
- the computing device 10 as illustrated in FIG. 1 b may include one or more modules, sub-modules, and various other components. As shown, the computing device 10 may include at least a sensor originated reported aspect providing module 102 (which may further include one or more sub-modules as illustrated in FIG. 2 a ) and a template development module 104 (which may also include one or more sub-modules as illustrated in FIG. 2 b ).
- the computing device 10 may further include a presentation module 106 (which may further include a transmission module 236 and/or a user interface indication module 238 ) and a memory 116 (which may store a plurality of reported aspects 15 that may further include one or more relevant reported aspects 16 and/or one or more non-relevant reported aspects 17 , one or more end user relevancy indications 142 , one or more source user relevancy indications 144 , one or more third party source relevancy indications 145 , one or more predefined time increment indications 146 , and/or one or more applications 140 ).
- a presentation module 106 which may further include a transmission module 236 and/or a user interface indication module 238
- a memory 116 which may store a plurality of reported aspects 15 that may further include one or more relevant reported aspects 16 and/or one or more non-relevant reported aspects 17 , one or more end user relevancy indications 142 , one or more source user relevancy indications 144 , one or more third party source relevancy indications 145
- the computing device 10 may also include, in various embodiments, a network interface 118 (e.g., a network interface card or NIC), a user interface 120 , a social networking entry reception module 110 (which may further include a blog entry reception module 111 and/or a status report reception module 112 ), a journal entry reception module 114 , and/or one or more sensors 240 a .
- a network interface 118 e.g., a network interface card or NIC
- a user interface 120 e.g., a network interface card or NIC
- a social networking entry reception module 110 which may further include a blog entry reception module 111 and/or a status report reception module 112
- a journal entry reception module 114 e.g., a journal entry reception module 114
- one or more sensors 240 a e.g., a sensor 240 .
- the presence or absence of some of these modules and sub-modules may depend on, for example, whether the computing device 10 is a server
- the sensor originated reported aspect providing module 102 may be configured to, among other things, provide (e.g., acquire from a memory 116 and/or from a wireless network and/or a wired network 50 ) one or more reported aspects 15 associated with one or more source users 2 * that were originally reported by one or more sensors 240 *.
- the template development module 104 may be configured to, among other things, develop one or more templates 18 designed to facilitate one or more end users 4 * to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates 18 are emulated, the development of the one or more templates 18 being based at least on a portion of the one or more reported aspects 15 .
- the memory 116 may be designed to store various data including a plurality of reported aspects 15 associated with one or more source user 2 *.
- the plurality of reported aspects 15 stored in the memory 116 may include one or more reported aspects 15 that were originally reported by one or more sensors 240 * and in some cases, another one or more reported aspects 15 that were originally reported by the one or more source users 2 *.
- the plurality of reported aspects 15 stored in memory 116 may include, in various implementations, one or more relevant reported aspects 16 that are relevant to achieving one or more target outcomes and/or one or more non-relevant reported aspects 17 that may not be relevant for achieving the one or more target outcomes.
- Other types of data may be stored in the memory 116 in various implementations including, for example, one or more end user relevancy indications 142 (e.g., one or more indications that indicate the types of reported aspects 15 that an end user 4 has an interest in or believes is relevant to achieving one or more target outcomes) and/or one or more source user relevancy indications 144 (e.g., one or more indications provided by a source user 2 * that indicate at least which types of reported aspects 15 are relevant to achieving one or more target outcomes).
- end user relevancy indications 142 e.g., one or more indications that indicate the types of reported aspects 15 that an end user 4 has an interest in or believes is relevant to achieving one or more target outcomes
- source user relevancy indications 144 e.g., one or more indications provided by a source user 2 * that indicate at least which types of reported aspects 15 are relevant to achieving one or more target outcomes.
- the memory 116 may also include, for example, one or more third party source relevancy indications 145 (e.g., one or more indications provided by one or more third party sources such as one or more third parties 6 that indicate at least which types of reported aspects 15 are relevant to achieving one or more target outcomes), one or more predefined time increment indications 146 (e.g., one or more indications that indicate at least one time increment, such as a time interval or window, that may be considered in order to determine whether, for example, a reported aspect 15 is relevant for achieving a target outcome if the reported aspect 15 indicates an aspect that occurred within the time increment from an occurrence of the target outcome as successfully achieved by, for example, a source user 2 *), and/or one or more applications 140 (e.g., a text messaging application, an instant messaging application, an email application, a social networking application, a voice recognition system, a Web 1.0 application, and/or Web 2.0 application to facilitate in communicating via, for example, the World Wide Web).
- third party source relevancy indications 145
- the memory 116 may comprise of one or more of a mass storage device, a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a cache memory such as random access memory (RAM), a flash memory, a synchronous random access memory (SRAM), a dynamic random access memory (DRAM), and/or other types of memory devices.
- ROM read-only memory
- PROM programmable read-only memory
- EPROM erasable programmable read-only memory
- RAM random access memory
- flash memory a flash memory
- SRAM synchronous random access memory
- DRAM dynamic random access memory
- the social networking entry reception module 110 may be configured to receive social networking entries from one or more sources including, for example, from one or more source users 2 *, from one or more end users 4 *, from one or more third parties 6 , from one or more sensor integrated devices 40 , and/or from one or more network servers 60 .
- the social networking entry reception module 110 may further include a blog entry reception module 111 for receiving blog entries (e.g. microblog entries) and/or a status report reception module 112 for receiving social networking status reports.
- the journal entry reception module 114 may be configured to receive journal entries from, for example, one or more source users 2 *, one or more end users 4 *, and/or one or more third parties 6 (e.g., a non-user).
- the user interface 120 may include one or more of, for example, a display monitor, a touchscreen, a keyboard, a keypad, a mouse, an audio system including one or more speakers, a microphone, an image capturing device such as a digital camera, and so forth.
- FIG. 2 a illustrates particular implementations of the sensor originated reported aspect providing module 102 of the computing device 10 of FIG. 1 b .
- the sensor originated reported aspect providing module 102 may include, in various implementations, one or more sub-modules.
- the sensor originated reported aspect providing module 102 may include a sensor originated reported aspect direct acquiring module 202 , a sensor originated reported aspect network acquiring module 204 , a sensor originated reported aspect memory acquiring module 206 , and/or a relevant reported aspect acquiring module 208 (which may further include a source user associated reported aspect acquiring module 210 and/or a relevancy factor relevant reported aspect acquiring module 212 ).
- the sensor originated reported aspect direct acquiring module 202 may be configured to acquire one or more reported aspects 15 directly from one or more sensors 240 a (e.g., as may be the case when the computing device 10 is a source user device).
- the sensor originated reported aspect network acquiring module 204 may be configured to acquire one or more reported aspects 15 via at least one of a wireless network and a wired network 50 .
- the sensor originated reported aspect memory acquiring module 206 may be configured to acquire one or more reported aspects 15 from the memory 116 .
- the relevant reported aspect acquiring module 208 may be configured to, among other things, selectively acquire one or more relevant reported aspects 16 that were originally reported by the one or more sensors 240 * and that are relevant with respect to achieving the one or more target outcomes.
- the relevant reported aspect acquiring module 208 may further include the source user associated reported aspect acquiring module 210 that is configured to selectively acquire one or more reported aspects 15 that were originally reported by one or more sensors 240 * and that are associated with one or more source users 2 * who have achieved the one or more target outcomes.
- the relevant reported aspect acquiring module 208 may include the relevancy factor relevant reported aspect acquiring module 212 that may be configured to, among other things, selectively acquire one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are relevant with respect to one or more relevancy factors (e.g., indications provided by an end user 4 * that indicates that only particular types of user behaviors such as dietary behaviors are relevant).
- the relevancy factor relevant reported aspect acquiring module 212 may be configured to, among other things, selectively acquire one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are relevant with respect to one or more relevancy factors (e.g., indications provided by an end user 4 * that indicates that only particular types of user behaviors such as dietary behaviors are relevant).
- FIG. 2 b illustrates particular implementations of the template development module 104 of FIG. 1 b .
- the template development module 104 may include one or more sub-modules.
- the template development module 104 may include an emulatable aspect including module 220 , a relationship defining module 222 , an emulatable intermediate outcome including module 223 , a plausible determining module 224 (which may further include an action module 226 that may further include a not plausible notification module 228 and/or a template modification module 229 ), and/or a relevant reported aspect identification module 230 (which may further include a source user associated reported aspect identification module 232 and/or a relevancy factor relevant reported aspect identification module 234 ).
- the emulatable aspect including module 220 may be configured to include into each of one or more templates 18 to be developed one or more emulatable aspects that correspond to at least a portion of one or more reported aspects 15 that may be provided by the sensor originated reported aspect providing module 102 .
- the relationship defining module 222 may be configured to define in each of the one or more templates 18 to be developed at least one temporal, specific time, or spatial relationship between at least two of the plurality of emulatable aspects that may be included in each of the one or more templates 18 .
- the emulatable intermediate outcome including module 223 may be configured to include into the one or more templates 18 to be developed one or more emulatable intermediate outcomes that are associated with the one or more target outcomes, for example, if one of the target outcomes is to lose 20 pounds of body weight, an emulatable intermediate outcome might be a weight loss of 10 pounds at the midway point of the template 18 to be developed.
- the plausible determining module 224 may be configured to determine whether at least one of one or more emulatable aspects to be included in the one or more templates 18 to be developed is a plausible aspect that has been successfully emulated by one or more third parties 6 , and if not plausible, prompting for example the action module 226 to execute one or more actions.
- the not plausible notification module 228 that may be included in the action module 226 may be configured to notify, in response to a determination that the at least one of the one or more emulatable aspects to be included in the one or more templates 18 is not a plausible aspect, at least one of an end user 4 *, a source user 2 *, and a third party 6 regarding the determination that at least one of the one or more emulatable aspects to be included in the one or more templates 18 is not a plausible aspect.
- the template modification module 229 that may be included in the action module 226 may be configured to modify, in response to a determination that the at least one of the one or more emulatable aspects is not a plausible aspect, at least one of the one or more templates 18 by revising the at least one of the one or more emulatable aspects determined to be not a plausible aspect or by replacing the at least one of the one or more emulatable aspects determined to be not a plausible aspect with at least one replacement emulatable aspect that is a plausible aspect that has been successfully emulated by one or more third parties 6 .
- the relevant reported aspect identification module 230 may be included in the template development module 104 may be configured to identify from the one or more reported aspects 15 that are provided by the sensor originated reported aspect providing module 102 one or more relevant reported aspects 16 that were originally reported by the one or more sensors 240 * and that are relevant with respect to achieving the one or more target outcomes.
- the relevant reported aspect identification module 230 may include the source user associated reported aspect identification module 232 configured to identify one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are associated with one or more source users 2 * who have been determined to have achieved the one or more target outcomes.
- the relevant reported aspect identification module 230 may include a relevancy factor relevant reported aspect identification module 234 that is configured to identify one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are relevant with respect to one or more relevancy factors.
- the various relevancy factors that may be considered in determining relevancy of a reported aspect 15 with respect to achieving one or more target outcomes will be discussed in greater detail herein.
- the sensor integrated device 40 may include at least one or more sensors 240 c .
- the one or more sensors 240 that may be included in a sensor integrated device 40 (as well as the computing device 10 and/or one or more of the local source user devices 20 *) may be designed to sense or detect one or more aspects associated with one or more source users 2 *.
- the one or more sensors 240 may include one or more devices that can monitor a user's physiological characteristics such as blood pressure sensors, heart rate monitors, glucometers (e.g., blood glucose meter), and so forth.
- the sensor integrated device 40 may further include a network interface 242 (similar to the network interface 118 of the computing device 10 ), a memory 243 (similar to memory 116 of the computing device 10 ), and one or more functional components 244 .
- a network interface 242 similar to the network interface 118 of the computing device 10
- a memory 243 similar to memory 116 of the computing device 10
- one or more functional components 244 may include an engine, four tires, steering system, transmission system, and so forth.
- the various modules e.g., the sensor originated reported aspect providing module 102 , the template development module 104 , and so forth
- the various modules may be implemented using hardware, software, firmware, or any combination thereof.
- the sensor originated reported aspect providing module 102 and/or the template development module 104 may be implemented with a processor 802 (e.g., microprocessor, controller, and so forth) executing computer readable instructions 804 (e.g., computer program product) stored in a storage medium 806 (e.g., volatile or non-volatile memory) such as a signal-bearing medium as depicted in the computing device 10 of FIG. 8 .
- a storage medium 806 e.g., volatile or non-volatile memory
- ASIC application specific integrated circuit
- FIG. 3 illustrates an operational flow 300 representing example operations directed to, among other things, development of one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based, at least in part on at least a portion of one or more reported aspects associated with one or more source users that were originally reported by one or more sensors.
- FIG. 3 discussions and explanations of the operational flows will be provided with respect to the exemplary environment 100 described above as illustrated in FIGS. 1 a and 1 b , and/or with respect to other examples (e.g., as provided in FIGS. 2 a , 2 b , 2 c , and 2 d ) and contexts.
- the operational flows may be executed in a number of other environments and contexts, and/or in modified versions of FIGS. 1 a , 1 b , 2 a , 2 b , 2 c , and 2 d .
- the various operational flows are presented in the sequence(s) illustrated, it should be understood that the various operations may be performed in other orders other than those which are illustrated, or may be performed concurrently.
- FIG. 3 various operations may be depicted in a box-within-a-box manner. Such depictions may indicate that an operation in an internal box may comprise an optional example embodiment of the operational step illustrated in one or more external boxes. However, it should be understood that internal box operations may be viewed as independent operations separate from any associated external boxes and may be performed in any sequence with respect to all other illustrated operations, or may be performed concurrently.
- the operational flow 300 may move to a sensor originated reported aspect providing operation 302 for providing one or more reported aspects associated with one or more source users that were originally reported by one or more sensors.
- the sensor originated reported aspect providing module 102 of the computing device 10 of FIG. 1 b providing (e.g., acquiring, retrieving, finding, locating, soliciting for, and so forth) one or more reported aspects 15 associated with one or more source users 2 * that were originally reported (e.g., initially detected or sensed) by one or more sensors 240 *(e.g., sensors 240 * designed to sense one or more aspects associated with one or more source users 2 * including, for example, behavior aspects associated with the one or more source users 2 *).
- operational flow 300 may also include a template developing operation 304 for developing one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based at least on a portion of the one or more reported aspects.
- the template development module 104 of the computing device 10 developing one or more templates 18 designed to facilitate one or more end users 4 * to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates 18 are emulated, the development of the one or more templates 18 being based at least on a portion of the one or more reported aspects 15 .
- the sensor originated reported aspect providing operation 302 as well as the template developing operation 304 may be implemented in a number of different ways in various alternative implementations.
- FIGS. 4 a , 4 b , 4 c , 4 d , 4 e , and 4 f illustrate the various ways that the sensor originated reported aspect providing operation 302 of FIG. 3 may be executed in various alternative implementations.
- the one or more reported aspects to be provided by the sensor originated reported aspect providing operation 302 may be provided by acquiring the one or more reported aspects from a variety of sources.
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 402 for acquiring the one or more reported aspects directly from the one or more sensors as depicted in FIG. 4 a .
- the sensor originated reported aspect direct acquiring module 202 (see FIG. 2 a ) of the computing device 10 of FIG.
- the one or more reported aspects 15 directly (e.g., instead of through a wireless network and/or wired network 50 ) from the one or more sensors 240 a of the computing device 10 .
- the sensor originated reported aspect providing operation 302 may include an operation 403 for acquiring the one or more reported aspects via at least one of a wireless network and a wired network as depicted in FIG. 4 a .
- the sensor originated reported aspect network acquiring module 204 (see FIG. 2 a ) of the computing device 10 when the computing device 10 is a server (e.g., server embodiment) acquiring (e.g., receiving, soliciting for, searching for, and so forth) the one or more reported aspects 15 via at least one of a wireless network and a wired network 50 .
- the sensor originated reported aspect providing operation 302 may include an operation 404 for acquiring the one or more reported aspects from a memory as depicted in FIG. 4 a .
- the sensor originated reported aspect memory acquiring module 206 (see FIG. 2 a ) of the computing device 10 acquiring (e.g., retrieving, finding, locating, and so forth) the one or more reported aspects 15 from a memory 116 .
- the sensor originated reported aspect providing operation 302 may include an operation 405 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more behavior incidences associated with the one or more source users as depicted in FIG. 4 a .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 * including one or more reported aspects 15 that indicate one or more behavior incidences associated with the one or more source users 2 *.
- operation 405 may include one or more additional operations.
- operation 405 may include an operation 406 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more incidences of activities executed by the one or more source users as depicted in FIG. 4 a .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 * including one or more reported aspects 15 that indicate one or more incidences of activities (e.g., dietary activities, exercise activities, social activities, medical treatment activities including drug consumption, and so forth) executed by the one or more source users 2 *.
- activities e.g., dietary activities, exercise activities, social activities, medical treatment activities including drug consumption, and so forth
- operation 405 may include an operation 407 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more user attitudes or conduct associated with the one or more source users as depicted in FIG. 4 a .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 *(e.g., fMRI, fNIR, and so forth) including one or more reported aspects 15 that indicate one or more user attitudes or conduct associated with the one or more source users 2 *.
- the sensor originated reported aspect providing operation 302 may include an operation 408 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more incidences of one or more mental states associated with the one or more source users as depicted in FIG. 4 a .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 * including one or more reported aspects 15 that indicate one or more incidences of one or more mental states (e.g., anger, happiness or sadness, mental alertness, mental fatigue, ashamedy, and so forth) associated with the one or more source users 2 *.
- one or more mental states e.g., anger, happiness or sadness, mental alertness, mental fatigue, ashamedy, and so forth
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 409 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more incidences of one or more user physical characteristics associated with the one or more source users as depicted in FIG. 4 b .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 * including one or more reported aspects 15 that indicate one or more incidences of one or more user physical characteristics (e.g., hair color, skin complexion, hair style, tattoos, blood pressure, body weight, body fat level, and so forth) associated with the one or more source users 2 *.
- operation 409 may include an operation 410 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more incidences of one or more user physiological characteristics associated with the one or more source users as depicted in FIG. 4 b .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 * including one or more reported aspects 15 that indicate one or more incidences of one or more user physiological characteristics (e.g., heart rate, blood glucose level, blood circulation or volume, brain electrical activity, heart rate, and so forth) associated with the one or more source users 2 *.
- user physiological characteristics e.g., heart rate, blood glucose level, blood circulation or volume, brain electrical activity, heart rate, and so forth
- the sensor originated reported aspect providing operation 302 may include an operation 411 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more incidences of one or more user locations associated with the one or more source users as depicted in FIG. 4 b .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 * including one or more reported aspects 15 that indicate one or more incidences of one or more user locations (e.g., home, workplace, school, New York City, Italy, and so forth) associated with the one or more source users 2 *.
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 412 for providing the one or more reported aspects that were originally reported by the one or more sensors including one or more reported aspects that indicate one or more incidences of one or more external events associated with the one or more source users as depicted in FIG. 4 b .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 that were originally reported by the one or more sensors 240 * including one or more reported aspects 15 that indicate one or more incidences of one or more external events (e.g., local weather or atmospheric conditions, air or water quality levels, traffic conditions, and so forth) associated with the one or more source users 2 *.
- one or more external events e.g., local weather or atmospheric conditions, air or water quality levels, traffic conditions, and so forth
- the one or more reported aspects 15 provided through the sensor originated reported aspect providing operation 302 of FIG. 3 may in some cases include two or more reported aspects associated with two or more source users.
- the sensor originated reported aspect providing operation 302 may include an operation 413 for providing two or more reported aspects associated with two or more source users that were originally reported by the one or more sensors as depicted in FIG. 4 b .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing two or more reported aspects 15 associated with two or more source users 2 * that were originally reported by one or more sensors 240 *.
- the sensor originated reported aspect providing operation 302 may include an operation 414 for providing two or more reported aspects associated with two or more source users that were originally reported by two or more sensors as depicted in FIG. 4 b .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing two or more reported aspects 15 associated with two or more source users 2 * that were originally reported by two or more sensors 240 *.
- the sensor originated reported aspect providing operation 302 may involve selectively acquiring relevant reported aspects 16 that are relevant with respect to achieving one or more target outcomes rather than merely acquiring, for example, any reported aspects 15 that are determined to be associated with the one or more source users 2 * and that were originally reported by the one or more sensors 240 *.
- the sensor originated reported aspect providing operation 302 may include an operation 415 for providing the one or more reported aspects by selectively acquiring one or more relevant reported aspects that were originally reported by the one or more sensors and that are relevant with respect to achieving the one or more target outcomes as depicted in FIG. 4 c .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing the one or more reported aspects 15 by having the relevant reported aspect acquiring module 208 (see FIG. 2 a ) selectively acquiring (e.g., retrieving, finding, locating and so forth) one or more relevant reported aspects 16 that were originally reported by the one or more sensors 240 * and that are relevant with respect to achieving the one or more target outcomes.
- Operation 415 for selectively acquiring the one or more relevant reported aspects may be executed in a number of different ways in various alternative implementations.
- operation 415 may include an operation 416 for acquiring the one or more relevant reported aspects by selectively acquiring one or more reported aspects that were originally reported by the one or more sensors and that are associated with one or more source users who have achieved the one or more target outcomes as depicted in FIG. 4 c .
- the relevant reported aspect acquiring module 208 of the computing device 10 acquiring the one or more relevant reported aspects 16 by having the source user associated reported aspect acquiring module 210 selectively acquiring one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are associated with one or more source users 2 * who have achieved the one or more target outcomes.
- a process may be executed to first find reported aspects 15 that correspond (e.g., equivalent or substantially equivalent) to the one or more target outcomes, and second, upon finding such corresponding reported aspects 15 , identify the source users 2 * who are associated with the corresponding reported aspects. By doing so, those source users 2 * who have achieved the one or more target outcomes are identified.
- operation 415 may include an operation 417 for acquiring the one or more relevant reported aspects by selectively acquiring one or more reported aspects that were originally reported by the one or more sensors and that are relevant with respect to one or more relevancy factors as depicted in FIG. 4 c .
- the relevant reported aspect acquiring module 208 of the computing device 10 acquiring the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect acquiring module 212 (e.g., see FIG. 2 a ) selectively acquiring one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are relevant with respect to one or more relevancy factors.
- operation 417 may include an operation 418 for acquiring the one or more relevant reported aspects by selectively acquiring one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that belong to one or more aspect types that are of interest to the one or more end users as depicted in FIG. 4 c .
- the relevant reported aspect acquiring module 208 of the computing device 10 acquiring the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect acquiring module 212 (e.g., see FIG.
- operation 417 may include an operation 419 for acquiring the one or more relevant reported aspects by selectively acquiring one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that belong to one or more aspect types that have been indicated by at least one source user as being relevant to the achievement of the one or more target outcomes as depicted in FIG. 4 c .
- the relevant reported aspect acquiring module 208 of the computing device 10 acquiring the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect acquiring module 212 (e.g., see FIG.
- operation 417 may include an operation 420 for acquiring the one or more relevant reported aspects by selectively acquiring one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that belong to one or more aspect types that have been indicated by at least one third party source as being relevant to the achievement of the one or more target outcomes as depicted in FIG. 4 c .
- the relevant reported aspect acquiring module 208 of the computing device 10 acquiring the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect acquiring module 212 (e.g., see FIG.
- operation 417 may include an operation 421 for acquiring the one or more relevant reported aspects by selectively acquiring one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that occurred within one or more predefined time increments, respectively, from one or more achievements of the one or more target outcomes by the one or more source users who have achieved the one or more target outcomes as depicted in FIG. 4 c .
- the relevant reported aspect acquiring module 208 of the computing device 10 acquiring the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect acquiring module 212 (e.g., see FIG.
- reported aspects 15 that are associated with source users 2 * who have achieved the one or more target outcomes and that are relevant based on certain relevancy factors may, nevertheless, not be relevant to achieving the one or more target outcomes if they occurred well before (or well after) the achievement of the one or more target outcomes by the one or more source users 2 *.
- a reported aspect 15 may, in some cases, be relevant to the achievement of the one or more target outcomes only if it falls within some time increment (e.g., “predefined time increment”) from one or more occurrences of one or more reported achievements by the one or more source users 2 *(e.g., as reported through one or more reported aspects 15 ) of the one or more target outcomes.
- the length of the predefined time increments to be considered in determining relevancy may depend on a number of factors including, for example, the type of target outcomes being sought and/or the type of templates to be developed.
- the predefined time increments to be considered may be set by an end user 4 *, by a source user 2 *, and/or by a third party source (e.g., third party 6 ).
- the one or more reported aspects 15 to be provided through the sensor originated reported aspect providing operation 302 of FIG. 3 may have been originally reported by a variety of sensors 240 *.
- the sensor originated reported aspect providing operation 302 may include an operation 422 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by one or more sensors designed to sense one or more behavior aspects associated with the one or more source users as depicted by FIG. 4 d .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 *(e.g., behavior aspect sensors 246 ) designed to sense one or more behavior aspects associated with the one or more source users 2 *.
- operation 422 may include an operation 423 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more pedometers as depicted in FIG. 4 d .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more pedometers 247 .
- operation 422 may include an operation 424 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more accelerometers as depicted in FIG. 4 d .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more accelerometers 248 .
- operation 422 may include an operation 425 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense usage of one or more exercise equipment as depicted in FIG. 4 d .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., exercise equipment sensors 249 ) designed to sense usage of one or more exercise equipment (e.g., bicycle, treadmill, elliptical exercise machines, and so forth).
- operation 422 may include an operation 426 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense usage of one or more transportation vehicles as depicted in FIG. 4 d .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., transport vehicle sensors 250 ) designed to sense usage of one or more transportation vehicles.
- operation 422 may include an operation 427 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense usage of one or more household appliances as depicted in FIG. 4 d .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., household appliance sensors 251 ) designed to sense usage of one or more household appliances.
- operation 422 may include an operation 428 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense toilet usage as depicted in FIG. 4 d .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., toilet usage sensors 252 ) designed to sense toilet usage.
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 429 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense one or more physical characteristics of the one or more source users as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., user physical characteristic sensors 253 ) designed to sense one or more physical characteristics of the one or more source users 2 *.
- operation 429 may further include an operation 430 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense one or more physiological characteristics of the one or more source users as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., user physiological sensors 254 ) designed to sense one or more physiological characteristics of the one or more source users 2 *.
- user physiological sensors 254 include, for example, blood pressure monitors, blood glucose meters, heart rate monitors, functional near-infrared (fNIR) devices, functional magnetic resonance imaging (fMRI) devices, and so forth).
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 431 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more global positioning systems (GPSs) as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more global positioning systems (GPSs) 255 .
- GPSs global positioning systems
- the sensor originated reported aspect providing operation 302 may include an operation 432 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense one or more environmental conditions as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 * (e.g., environmental condition sensors 256 ) designed to sense one or more environmental conditions (e.g., source user environmental conditions).
- Operation 432 may, in turn, further include an operation 433 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense water quality as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., water quality sensors 259 ) designed to sense water quality (e.g., qualities of drinking water consumed by the one or more source users 2 *).
- operation 432 may include an operation 434 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense air quality as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., air quality sensors 257 such as particulate or pollen counter, gas detectors, and so forth) designed to sense air quality.
- operation 432 may include an operation 435 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense atmospheric conditions as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., atmospheric condition sensors 258 ) designed to sense atmospheric conditions.
- operation 435 may further include an operation 436 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including at least one of a barometer, a thermometer, and a humidity sensor as depicted in FIG. 4 e .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including at least one of a barometer, a thermometer, and a humidity sensor.
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 437 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more sensors designed to sense one or more physiological characteristics used to determine one or more mental states as depicted in FIG. 4 f .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more sensors 240 *(e.g., mental state sensors 260 ) designed to sense one or more physiological characteristics used to determine one or more mental states.
- Examples of mental state sensors 260 that can sense one or more physiological characteristics that may be used in order to determine mental states include, for example, fNIR devices, fMRI devices, electroencephalography (EEG) devices, magnetoencephalography (MEG) devices, galvanic skin sensor devices, respiration sensor devices, and so forth).
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 438 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors including one or more image capturing devices as depicted in FIG. 4 f .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * including one or more image capturing devices 261 (e.g., digital camera, digital camcorder, ultrasound devices, and so forth).
- Such image capturing devices 261 may be employed in some implementations in order to capture images of various aspects (e.g., user activities or facial expressions) associated with one or more source users 2 *.
- data provided by such image capturing devices 261 may be interpreted using, for example, image interpretation software (e.g., facial recognition applications).
- the sensor originated reported aspect providing operation 302 of FIG. 3 may include an operation 439 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors and via one or more social networking entries as depicted in FIG. 4 f .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by one or more sensors 240 * and via one or more social networking entries.
- operation 439 may further include an operation 440 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors via one or more blog entries as depicted in FIG. 4 f .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by the one or more sensors 240 * via one or more blog entries (e.g., microblog entries).
- operation 439 may include an operation 441 for providing one or more reported aspects associated with the one or more source users that were at least originally reported by the one or more sensors via one or more status reports as depicted in FIG. 4 f .
- the sensor originated reported aspect providing module 102 of the computing device 10 providing one or more reported aspects 15 associated with the one or more source users 2 * that were at least originally reported by the one or more sensors 240 * via one or more status reports (e.g., social networking status reports).
- the template developing operation 304 may be executed in a number of different ways as illustrated in FIGS. 5 a , 5 b , 5 c , and 5 d .
- the template developing operation 304 may include an operation 542 for including into each of the one or more templates one or more emulatable aspects that correspond to at least the portion of the one or more reported aspects as depicted in FIG. 5 a .
- the emulatable aspect including module 220 (see FIG. 2 b ) of the computing device 10 including into each of the one or more templates 18 one or more emulatable aspects that correspond to at least the portion of the one or more reported aspects 15 .
- operation 542 may further include one or more additional operations in various alternative implementations.
- operation 542 may include an operation 543 for including into each of the one or more templates a plurality of emulatable aspects that correspond to a plurality of reported aspects associated with the one or more source users and that were originally reported by the one or more sensors as depicted in FIG. 5 a .
- operation 543 may, in turn, further include an operation 544 for defining in each of the one or more templates one or more relationships between the plurality of emulatable aspects included in each of the one or more templates as depicted in FIG. 5 a .
- the relationship defining module 222 (see FIG. 2 b ) of the computing device 10 defining in each of the one or more templates 18 at least one temporal, specific time, or spatial relationship between the plurality of emulatable aspects included in each of the one or more templates 18 .
- operation 544 may further include an operation 545 for defining in each of the one or more templates at least one temporal, specific time, or spatial relationship between at least two of the plurality of emulatable aspects included in each of the one or more templates as depicted in FIG. 5 a .
- the relationship defining module 222 of the computing device 10 defining in each of the one or more templates 18 at least one temporal, specific time, or spatial relationship between at least two of the plurality of emulatable aspects included in each of the one or more templates 18 .
- the operation 542 for including into each of the one or more templates 18 one or more emulatable aspects may include an operation 546 for determining whether at least one of the one or more emulatable aspects to be included in the one or more templates is a plausible aspect that has been successfully emulated by one or more third parties, and if not plausible, execute one or more actions as depicted in FIG. 5 a .
- the plausible determining module 224 see FIG.
- operation 546 may include an operation 547 for notifying, in response to determining that the at least one of the one or more emulatable aspects to be included in the one or more templates is not a plausible aspect, at least one of an end user, a source user, and a third party regarding the determination that at least one of the one or more emulatable aspects to be included in the one or more templates is not a plausible aspect as depicted in FIG. 5 a .
- the not plausible notification module 228 see FIG.
- the computing device 10 notifying (e.g., transmitting or indicating a notification), in response to determining that the at least one of the one or more emulatable aspects to be included in the one or more templates 18 is not a plausible aspect, at least one of an end user 4 *, a source user 2 *, and a third party 6 regarding the determination that at least one of the one or more emulatable aspects to be included in the one or more templates 18 is not a plausible aspect.
- operation 546 may include an operation 548 for modifying, in response to determining that the at least one of the one or more emulatable aspects is not a plausible aspect, at least one of the one or more templates by revising the at least one of the one or more emulatable aspects determined to be not a plausible aspect or by replacing the at least one of the one or more emulatable aspects determined to be not a plausible aspect with at least one replacement emulatable aspect that is a plausible aspect that has been successfully emulated by one or more third parties as depicted in FIG. 5 a .
- the template modification module 229 see FIG.
- the computing device 10 modifying, in response to determining that the at least one of the one or more emulatable aspects is not a plausible aspect, at least one of the one or more templates 18 by revising the at least one of the one or more emulatable aspects determined to be not a plausible aspect or by replacing the at least one of the one or more emulatable aspects determined to be not a plausible aspect with at least one replacement emulatable aspect that is a plausible aspect that has been successfully emulated by one or more third parties 6 .
- the one or more third parties 6 may merely be other end users 4 * who may have previously attempted to emulate the one or more templates 18 .
- operation 546 may include an operation 549 for determining whether at least one of the one or more emulatable aspects to be included in the one or more templates is a plausible aspect that has been successfully emulated by the one or more third parties in order to achieve at least one of the one or more target outcomes, and if not plausible, execute the one or more actions as depicted in FIG. 5 a .
- the plausible determining module 224 of the computing device 10 determining whether at least one of the one or more emulatable aspects to be included in the one or more templates 18 is a plausible aspect that has been successfully emulated by the one or more third parties 6 in order to achieve at least one of the one or more target outcomes, and if not plausible, execute the one or more actions.
- the template developing operation 304 of FIG. 3 may involve identifying from the one or more reported aspects that were provided through operation 302 , one or more relevant reported aspects 16 that were at least originally reported by the one or more sensors 240 * and that are relevant with respect to achieving the one or more target outcomes.
- the template developing operation 304 may include an operation 550 for identifying from the one or more reported aspects one or more relevant reported aspects that were originally reported by the one or more sensors and that are relevant with respect to achieving the one or more target outcomes as depicted in FIG. 5 b .
- the relevant reported aspect identification module 230 (see FIG. 2 b ) of the computing device 10 identifying from the one or more reported aspects 15 one or more relevant reported aspects 16 that were originally reported by the one or more sensors 240 * and that are relevant with respect to achieving the one or more target outcomes.
- operation 550 may include an operation 551 for identifying from the one or more reported aspects the one or more relevant reported aspects by identifying one or more reported aspects that were originally reported by the one or more sensors and that are associated with one or more source users who have achieved the one or more target outcomes as depicted in FIG. 5 b .
- the relevant reported aspect identification module 230 of the computing device 10 identifying from the one or more reported aspects 15 the one or more relevant reported aspects 16 by having the source user associated reported aspect identification module 232 identifying one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are associated with one or more source users 2 * who have achieved the one or more target outcomes.
- Operation 551 may further include one or more additional operations in various alternative implementations.
- operation 551 may include an operation 552 for identifying from the one or more reported aspects the one or more relevant reported aspects by identifying one or more reported aspects that were originally reported by the one or more sensors and that are relevant with respect to one or more relevancy factors as depicted in FIG. 5 b .
- the relevant reported aspect identification module 230 of the computing device 10 identifying from the one or more reported aspects 15 the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect identification module 234 identifying one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that are relevant with respect to one or more relevancy factors.
- operation 552 may further include an operation 553 for identifying from the one or more reported aspects the one or more relevant reported aspects by identifying one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that belong to one or more aspect types that are of interest to the one or more end users as depicted in FIG. 5 b .
- the relevant reported aspect identification module 230 of the computing device 10 identifying from the one or more reported aspects 15 the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect identification module 234 identifying one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that indicate one or more aspects that belong to one or more aspect types that are of interest to the one or more end users 4 *.
- operation 552 may include an operation 554 for identifying from the one or more reported aspects the one or more relevant reported aspects by identifying one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that belong to one or more aspect types that have been indicated by at least one source user as being relevant to the achievement of the one or more target outcomes as depicted in FIG. 5 b .
- the relevant reported aspect identification module 230 of the computing device 10 identifying from the one or more reported aspects 15 the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect identification module 234 identifying one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that indicate one or more aspects that belong to one or more aspect types that have been indicated by at least one source user 2 * as being relevant to the achievement of the one or more target outcomes.
- operation 552 may include an operation 555 for identifying from the one or more reported aspects the one or more relevant reported aspects by identifying one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that belong to one or more aspect types that have been indicated by at least one third party source as being relevant to the achievement of the one or more target outcomes as depicted in FIG. 5 b .
- the relevant reported aspect identification module 230 of the computing device 10 identifying from the one or more reported aspects 15 the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect identification module 234 identifying one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that indicate one or more aspects that belong to one or more aspect types that have been indicated by at least one third party source (e.g. a third party 6 , a content provider, or a publication) as being relevant to the achievement of the one or more target outcomes.
- a third party source e.g. a third party 6 , a content provider, or a publication
- operation 552 may include an operation 556 for identifying from the one or more reported aspects the one or more relevant reported aspects by identifying one or more reported aspects that were originally reported by the one or more sensors and that indicate one or more aspects that occurred within one or more predefined time increments, respectively, from one or more achievements of the one or more target outcomes by the one or more source users who have achieved the one or more target outcomes as depicted in FIG. 5 b .
- the relevant reported aspect identification module 230 of the computing device 10 identifying from the one or more reported aspects 15 the one or more relevant reported aspects 16 by having the relevancy factor relevant reported aspect identification module 234 identifying one or more reported aspects 15 that were originally reported by the one or more sensors 240 * and that indicate one or more aspects that occurred within one or more predefined time increments, respectively, from one or more achievements (e.g., occurrences) of the one or more target outcomes by the one or more source users 2 * who have achieved the one or more target outcomes.
- the template developing operation 304 of FIG. 3 may include an operation 557 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more health or medical outcomes as depicted in FIG. 5 c .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more health or medical outcomes (e.g., recover from a particular illness, avoid acquiring certain illnesses such as cancer or influenza, obtain improved physiological traits, improve mental health, and so forth).
- the template developing operation 304 may include an operation 558 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more athletic outcomes as depicted in FIG. 5 c .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more athletic outcomes (e.g., finish a marathon, achieve a certain golf score, win a tennis tournament, and so forth).
- the template developing operation 304 may include an operation 559 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more gaming outcomes as depicted in FIG. 5 c .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more gaming outcomes (e.g., achieve a certain chase ranking, become proficient at a particular electronic game, and so forth).
- the template developing operation 304 may include an operation 560 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more occupational outcomes as depicted in FIG. 5 c .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more occupational outcomes (e.g., finish a work project, get a promotion, develop a certain computer skill, develop a personal work network, and so forth).
- the template developing operation 304 may include an operation 561 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more social outcomes as depicted in FIG. 5 c .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more social outcomes (e.g., going out on a date, receive an invitation to join a particular social club, and so forth).
- the template developing operation 304 may include an operation 562 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more leisure outcomes as depicted in FIG. 5 d .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more leisure outcomes (e.g., going to Hawaii on a vacation, setting aside time for a vacation, finish reading a novel, spending time with offspring, and so forth).
- the template developing operation 304 may include an operation 563 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more sexual intimacy outcomes as depicted in FIG. 5 d .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more sexual intimacy outcomes (e.g., increase frequency and quality of sexual intimacy encounters).
- the template developing operation 304 may include an operation 564 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more psychological outcomes as depicted in FIG. 5 d .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more psychological outcomes (e.g., develop better self-esteem, be cured of a phobia, and so forth).
- the template developing operation 304 may include an operation 565 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more intellectual or academic outcomes as depicted in FIG. 5 d .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more intellectual or academic outcomes (e.g., achieve a certain score for a test, graduate or be accepted from a particular school, win a particular academic award, and so forth).
- the template developing operation 304 may include an operation 566 for developing the one or more templates including at least one template that is designed to facilitate the one or more end users to achieve one or more user states as depicted in FIG. 5 d .
- the template development module 104 of the computing device 10 developing the one or more templates 18 including at least one template 18 that is designed to facilitate one or more end users 4 * to achieve one or more user states (e.g., be content, be relaxed, be focused, and so forth).
- the template developing operation 304 of FIG. 3 may involve developing one or more templates 18 based on data provided by sensors 240 * and data provided by source users 2 *.
- the template developing operation 304 may include an operation 567 for developing the one or more templates based at least on the portion of the one or more reported aspects and on another one or more reported aspects that are associated with the one or more source users and that were originally reported by the one or more source users as depicted in FIG. 5 d .
- the template development module 104 of the computing device 10 developing the one or more templates 18 based at least on the portion of the one or more reported aspects 15 and on another one or more reported aspects 15 that are associated with the one or more source users 2 * and that were originally reported by the one or more source users 2 *.
- operation 567 may further include an operation 568 for developing the one or more templates based at least on the portion of the one or more reported aspects and on another one or more reported aspects that are associated with the one or more source users and that were originally reported by the one or more source users via one or more social networking entries as depicted in FIG. 5 d .
- the template development module 104 of the computing device 10 developing the one or more templates 18 based at least on the portion of the one or more reported aspects 15 and on another one or more reported aspects 15 that are associated with the one or more source users 2 * and that were originally reported by the one or more source users 2 * via one or more social networking entries (e.g., blog entries such as microblog entries, status reports, and so forth).
- social networking entries e.g., blog entries such as microblog entries, status reports, and so forth.
- Operational flow 600 includes certain operations that mirror the operations included in the operational flow 300 of FIG. 3 . These operations include a sensor originated reported aspect providing operation 602 and a template developing operation 604 that corresponds to and mirror the sensor originated reported aspect providing operation 302 and the template developing operation 304 , respectively, of FIG. 3 .
- operational flow 300 includes a template presenting operation 606 for presenting the one or more templates as depicted in FIG. 6 .
- the presentation module 106 of the computing device 10 presenting the one or more templates 18 to one or more end users 4 *, to one or more source users 2 *, to one or more third parties 6 , or to one or more network servers 60 .
- the template presentation operation 606 may include an operation 770 for transmitting the one or more templates via at least one of a wireless network and a wired network as depicted in FIG. 7 .
- the transmission module 236 of the computing device 10 transmitting the one or more templates 18 via at least one of a wireless network and a wired network 50 .
- the template presentation operation 606 may include an operation 771 for indicating the one or more templates via a user interface as depicted in FIG. 7 .
- the user interface indication module 238 indicating (e.g., displaying or audioally indicating) the one or more templates 18 via a user interface 120 (e.g., a display monitor, a touch screen, and/or one or more audio speakers).
- FIG. 8 is a high-level block diagram illustrating a particular implementation of the computing device 10 of FIG. 1 b .
- the computing device 10 may include a processor 802 (e.g., microprocessor, controller, and so forth) coupled to storage medium 806 (e.g., volatile or non-volatile memory).
- the storage medium 806 may store computer readable instructions 804 (e.g., computer program product).
- the processor 802 may execute the computer readable instructions 804 in order to execute one or more operations described above and as illustrated in FIGS. 3 , 4 a , 4 b , 4 c , 4 d , 4 e , 4 f , 5 a , 5 b , 5 c , and 5 d.
- the processor 802 may execute the computer readable instructions 804 in order to provide one or more reported aspects 15 associated with one or more source users 2 * that were originally reported by one or more sensors 240 *; and/or to develop one or more templates 18 designed to facilitate one or more end users 4 * to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates 18 are emulated, the development of the one or more templates 18 being based at least on a portion of the one or more reported aspects 15 as illustrated by the operational flow 300 of FIG. 3 .
- an implementer may opt for a mainly hardware and/or firmware vehicle; alternatively, if flexibility is paramount, the implementer may opt for a mainly software implementation; or, yet again alternatively, the implementer may opt for some combination of hardware, software, and/or firmware.
- any vehicle to be utilized is a choice dependent upon the context in which the vehicle will be deployed and the specific concerns (e.g., speed, flexibility, or predictability) of the implementer, any of which may vary.
- Those skilled in the art will recognize that optical aspects of implementations will typically employ optically-oriented hardware, software, and or firmware.
- a signal bearing medium examples include, but are not limited to, the following: a recordable type medium such as a floppy disk, a hard disk drive, a Compact Disc (CD), a Digital Video Disk (DVD), a digital tape, a computer memory, etc.; and a transmission type medium such as a digital and/or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).
- electrical circuitry includes, but is not limited to, electrical circuitry having at least one discrete electrical circuit, electrical circuitry having at least one integrated circuit, electrical circuitry having at least one application specific integrated circuit, electrical circuitry forming a general purpose computing device configured by a computer program (e.g., a general purpose computer configured by a computer program which at least partially carries out processes and/or devices described herein, or a microprocessor configured by a computer program which at least partially carries out processes and/or devices described herein), electrical circuitry forming a memory device (e.g., forms of random access memory), and/or electrical circuitry forming a communications device (e.g., a modem, communications switch, or optical-electrical equipment).
- a computer program e.g., a general purpose computer configured by a computer program which at least partially carries out processes and/or devices described herein, or a microprocessor configured by a computer program which at least partially carries out processes and/or devices described herein
- electrical circuitry forming a memory device
- a typical data processing system generally includes one or more of a system unit housing, a video display device, a memory such as volatile and non-volatile memory, processors such as microprocessors and digital signal processors, computational entities such as operating systems, drivers, graphical user interfaces, and applications programs, one or more interaction devices, such as a touch pad or screen, and/or control systems including feedback loops and control motors (e.g., feedback for sensing position and/or velocity; control motors for moving and/or adjusting components and/or quantities).
- a typical data processing system may be implemented utilizing any suitable commercially available components, such as those typically found in data computing/communication and/or network computing/communication systems.
- any two components so associated can also be viewed as being “operably connected”, or “operably coupled”, to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being “operably couplable”, to each other to achieve the desired functionality.
- operably couplable include but are not limited to physically mateable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interacting and/or logically interactable components.
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Abstract
Description
Claims (45)
Priority Applications (12)
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US12/592,946 US8244553B2 (en) | 2009-09-03 | 2009-12-04 | Template development based on sensor originated reported aspects |
US12/653,117 US8255236B2 (en) | 2009-09-03 | 2009-12-07 | Source user based provision of one or more templates |
US12/653,180 US8255237B2 (en) | 2009-09-03 | 2009-12-08 | Source user based provision of one or more templates |
US12/653,387 US8311846B2 (en) | 2009-09-03 | 2009-12-10 | Target outcome based provision of one or more templates |
US12/653,386 US8260625B2 (en) | 2009-09-03 | 2009-12-11 | Target outcome based provision of one or more templates |
US12/653,972 US8260626B2 (en) | 2009-09-03 | 2009-12-17 | Detecting deviation from compliant execution of a template |
US12/655,075 US8265944B2 (en) | 2009-09-03 | 2009-12-21 | Detecting deviation from compliant execution of a template |
US12/655,250 US8265945B2 (en) | 2009-09-03 | 2009-12-23 | Template modification based on deviation from compliant execution of the template |
US12/655,365 US8265946B2 (en) | 2009-09-03 | 2009-12-28 | Template modification based on deviation from compliant execution of the template |
US12/655,582 US8321233B2 (en) | 2009-09-03 | 2009-12-30 | Template development based on reported aspects of a plurality of source users |
US12/655,581 US8275629B2 (en) | 2009-09-03 | 2009-12-31 | Template development based on reported aspects of a plurality of source users |
US13/656,288 US20130144919A1 (en) | 2009-09-03 | 2012-10-19 | Template development based on reported aspects of a plurality of source users |
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US12/584,489 US8265943B2 (en) | 2009-09-03 | 2009-09-03 | Personalized plan development |
US12/584,653 US8280746B2 (en) | 2009-09-03 | 2009-09-08 | Personalized plan development |
US12/587,018 US8260624B2 (en) | 2009-09-03 | 2009-09-29 | Personalized plan development based on outcome identification |
US12/587,127 US8229756B2 (en) | 2009-09-03 | 2009-09-30 | Personalized plan development based on outcome identification |
US12/590,027 US8275628B2 (en) | 2009-09-03 | 2009-10-29 | Personalized plan development based on one or more reported aspects' association with one or more source users |
US12/590,039 US8392205B2 (en) | 2009-09-03 | 2009-10-30 | Personalized plan development based on one or more reported aspects' association with one or more source users |
US12/590,600 US8234123B2 (en) | 2009-09-03 | 2009-11-10 | Personalized plan development based on identification of one or more relevant reported aspects |
US12/590,841 US8249887B2 (en) | 2009-09-03 | 2009-11-12 | Personalized plan development based on identification of one or more relevant reported aspects |
US12/592,075 US8255400B2 (en) | 2009-09-03 | 2009-11-17 | Development of personalized plans based on acquisition of relevant reported aspects |
US12/592,161 US8249888B2 (en) | 2009-09-03 | 2009-11-18 | Development of personalized plans based on acquisition of relevant reported aspects |
US12/592,544 US8260807B2 (en) | 2009-09-03 | 2009-11-24 | Identification and provision of reported aspects that are relevant with respect to achievement of target outcomes |
US12/592,548 US8271524B2 (en) | 2009-09-03 | 2009-11-25 | Identification and provision of reported aspects that are relevant with respect to achievement of target outcomes |
US12/592,944 US8244552B2 (en) | 2009-09-03 | 2009-12-03 | Template development based on sensor originated reported aspects |
US12/592,946 US8244553B2 (en) | 2009-09-03 | 2009-12-04 | Template development based on sensor originated reported aspects |
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US12/592,944 Continuation-In-Part US8244552B2 (en) | 2009-09-03 | 2009-12-03 | Template development based on sensor originated reported aspects |
US12/653,117 Continuation-In-Part US8255236B2 (en) | 2009-09-03 | 2009-12-07 | Source user based provision of one or more templates |
US12/655,250 Continuation-In-Part US8265945B2 (en) | 2009-09-03 | 2009-12-23 | Template modification based on deviation from compliant execution of the template |
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US12/655,582 Continuation-In-Part US8321233B2 (en) | 2009-09-03 | 2009-12-30 | Template development based on reported aspects of a plurality of source users |
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